---
title: "ASA>3 mo only(NSAID 제외): 위암"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
editor_options: 
  chunk_output_type: console
---
```{r setup, include=FALSE}
options(htmltools.dir.version = FALSE)
knitr::opts_chunk$set(echo = FALSE, fig.align = "center")
library(knitr);library(DT);library(dplyr);library(data.table);library(flexdashboard);library(kableExtra)

#setwd("/home/js/Homepage/cdmkdh/docs")
ref <- readRDS(paste0("result/outcomeModelReference.rds"))
fig.att <- grep("attritionDiagram", list.files("result"), value = T)
fig.attstrata <- grep("Strata", fig.att, value = T)
fig.att <- list(setdiff(fig.att, fig.attstrata), fig.attstrata)
    
fig.covbal <- grep("covBal", list.files("result"), value = T)
fig.covalscatter <- grep("Scatter", fig.covbal, value = T)
fig.covbal <-list(setdiff(fig.covbal, fig.covalscatter), fig.covalscatter)
      
fig.psplot <- grep("propensityScorePlot", list.files("result"), value = T) 
fig.psstrata <- grep("Strata", fig.psplot, value = T)
fig.psplot <- list(setdiff(fig.psplot, fig.psstrata), fig.psstrata)
    
fig.km <-  grep("kaplanMeier", list.files("result"), value = T) 
```


Study flow
=======================================================================

Column
-----------------------------------------------------------------------

### Before matching

```{r}
include_graphics(paste0("result/",fig.att[[1]][1]))

```


### After matching

```{r}
include_graphics(paste0("result/",fig.att[[2]][1]))

```




Matching info
=======================================================================

Column{.tabset}
-----------------------------------------------------------------------

### Balance table

```{r}
out.bal <- readRDS(paste0(getwd(), ref$covariateBalanceFile))
it <- 2
ic <- 3
bal.before <- sapply(c(it, ic), function(x){paste0(out.bal[, x + 2], " (", round(100 * out.bal[, x], 1), "%)")})
bal.after <- sapply(c(it, ic), function(x){paste0(out.bal[, x + 7], " (", round(100 * out.bal[, x + 5], 1), "%)")})
    
out.tb <- data.frame(out.bal[, 12], bal.before, round(out.bal[, 15], 1 + 2), bal.after, round(out.bal[, 16], 1 + 2), out.bal[, c(1, 13, 14)])
out.tb[out.tb == "NA (NA%)"] <- NA
names(out.tb)[1:7] <- c("Covariate", "Treated_before", "Comparator_before", "SMD_before", "Treated_after", "Comparator_after", "SMD_after")

datatable(out.tb, rownames = F, filter = "top", extensions= "Buttons", caption = "Balance table for PS matching", 
              options = c(jstable::opt.data("data_balance"), list(scrollX = TRUE))) 
```


### Balance plot

```{r}
include_graphics(paste0("result/",fig.covbal[[1]][1]))
```

### SMD distribution

```{r}
include_graphics(paste0("result/",fig.covbal[[2]][1]))
```

### PS distributuin

```{r,  fig.show = "hold", out.width = "50%", fig.align = "default"}
include_graphics(paste0("result/",fig.psplot[[1]][1]))
include_graphics(paste0("result/",fig.psplot[[2]][1]))
```


Model outcome
=======================================================================

```{r, include=F}
res <- readRDS(paste0(getwd(), ref$outcomeModelFile))
```

Column{.tabset}
-----------------------------------------------------------------------

### Kaplan-meier plot

```{r}
include_graphics(paste0("result/", "kaplanMeier.png"))
```

### Cox result

```{r}
hr <- res$outcomeModelTreatmentEstimate
pv <- 2 * (1 - pnorm(abs(hr$logRr/hr$seLogRr)))
pv <- ifelse(pv < 0.001, "< 0.001", round(pv, 3))
tb.hr <- data.table(`HR (95% CI)` = paste0(round(exp(hr$logRr), 2), " (", round(exp(hr$logLb95), 2), "-", round(exp(hr$logUb95), 2), ")"), `P value` = pv)
kable(tb.hr, row.names = F, caption = "Hazard ratio") %>%
  kable_styling(full_width = F)

datatable(data.frame(Covariates = names(res[["psModelCoef"]]), HR = round(exp(res[["psModelCoef"]]), 2)),  rownames = F, filter = "top", extensions= "Buttons", caption = "PS model coefficients", 
          options = c(jstable::opt.data("psModelCoef"), list(scrollX = TRUE))) %>% 
  formatRound(2, digits = 3)
```

### Others

```{r}
tb.oth <- t(data.frame(as.integer(res$populationCounts[, 2:3]), as.integer(res$timeAtRisk), as.integer(res$outcomeCounts[5:6])))
colnames(tb.oth) <- c("Treated", "Comparator")
rownames(tb.oth) <- c("Population", "Time at Risk", "Event")

kable(tb.oth, row.names = T, caption = "Other info") %>%
  kable_styling(full_width = F)
```